18eb87f25f
Upsample grad ( #1420 )
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* encode size of upsample in enum
* working convolution method for limited 2d kernels
* add test for sf 3 interpolation
* add higher dimensional tests, fix to work with multichannel input
* Remove commented out line.
---------
Co-authored-by: Laurent <laurent.mazare@gmail.com >
2023-12-10 08:43:24 +01:00
60fdab4e17
Detach all grads during backprop. ( #1243 )
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* Detach all grads during backprop.
* Add an environment variable to select the backprop behavior.
* Update the comment.
2023-11-05 14:07:41 +01:00
7051fb8098
feat: add backprop for elu ( #1269 )
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* feat: add backprop for elu
* Cosmetic tweaks.
---------
Co-authored-by: Laurent <laurent.mazare@gmail.com >
2023-11-04 21:26:41 +01:00
3173b1ce3b
feat: impl backprop for erf and gelu-erf ( #1258 )
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* impl backprop for erf anf gelu-erf
* feat: unary tests added for erf and gelu-erf
* fix: (clippy) remove immediately dereferenced ref
* fix: improve comments with pytorch code snippet
* fix: adjust comment typo in backprop impl
2023-11-03 21:32:30 +01:00
1cfc5d6d0c
Backprop support for conv1d (cpu only for now). ( #1255 )
2023-11-03 14:23:53 +01:00
be4555c5a5
Add the conv-transpose1d op. ( #1251 )
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* Skeleton structure for conv-transpose1d.
* CPU implementation for conv-transpose1d.
2023-11-03 09:44:46 +01:00
46d6566c99
Fix the conv2d gradient computation. ( #1214 )
2023-10-29 09:50:04 +00:00
807e3f9f52
derivative for GELU ( #1160 )
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* derivative for GELU
* add tests
2023-10-23 20:23:45 +01:00
8f310cc666
Avoid trying to backprop through non-differentiable layers. ( #1094 )
2023-10-14 22:03:41 +01:00
c18a856e76
Add the rounding operators. ( #1030 )
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* Add the rounding operators.
* Avoid tracking gradients for the rounding operations.
* Add some rounding tests.
2023-10-04 17:58:44 +01:00
8601537e31
Add slice-scatter. ( #927 )
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* Add slice-scatter.
* Add the op.
* Make transpose be a no-op when the dimensions are identical.
* Add the backprop.
* And add some gradient test.
2023-09-22 12:18:16 +01:00
7b26e513f1
Add the erf function. ( #917 )
2023-09-21 06:19:10 +01:00
d7e48234d4
Add an erf based gelu op ( #900 )
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* Erf based gelu.
* Add the erf backed gelu.
* Test the new gelu op (which is not gelu_new).
2023-09-19 19:54:28 +01:00
635012d770
Do not backprop through argmin/argmax. ( #865 )
2023-09-15 22:15:40 +01:00
9a465e1b26
Add 1d upsampling. ( #839 )
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* Add 1d upsampling.
* Add the interpolate functions.
2023-09-13 16:50:39 +01:00
ad8a62dbf5
Add tanh. ( #675 )
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* Add tanh.
* Use tanh in the lstm block.
* Add a test for tanh forward and backward passes.
2023-08-30 13:54:50 +01:00
59b731de99
Add the powf op. ( #664 )
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* Add the powf op.
* Cuda kernels and backprop.
* Add a test.
2023-08-29 20:48:18 +01:00
2d3fcad267
Simplify usage of the pool functions. ( #662 )
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* Simplify usage of the pool functions.
* Small tweak.
* Attempt at using apply to simplify the convnet definition.
2023-08-29 19:12:16 +01:00
a044907ffc
Dilated convolutions ( #657 )
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* Add the dilation parameter.
* Restore the basic optimizer example.
* Dilation support in cudnn.
* Use the dilation parameter in the cpu backend.
* More dilation support.
* No support for dilation in transposed convolutions.
* Add dilation to a test.
* Remove a print.
* Helper function.
2023-08-29 16:12:11 +01:00
d0a330448d
Backprop support for pooling ops. ( #652 )
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* Backprop support for pooling ops.
* max-pool gradient.
2023-08-29 10:17:59 +01:00
b292047882
Backprop for conv2d. ( #638 )
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* Start adding backprop for conv2d.
* Backprop for conv2d.
* Bugfix + start adding a conv2d test.
* Conv2d backprop testing.
* More conv fixes.
2023-08-28 16:08:55 +01:00
3cca89cc70
Add conv-transpose. ( #635 )
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* Add conv-transpose.
* Return zeros for now.
* Naive CPU implementation.
* Add a conv-transpose test + fix the cpu implementation.
* Add a second test.
2023-08-28 10:10:12 +01:00
d70cffdab6
Fix the minimum/maximum gradient computations. ( #534 )
2023-08-21 08:28:41 +01:00
a1812f934f
Add a yolo-v3 example. ( #528 )
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* Add a couple functions required for yolo.
* Add the yolo-v3 example.
* Add minimum and maximum.
* Use the newly introduced maximum.
* Cuda support for min/max + add some testing.
* Allow for more tests to work with accelerate.
* Fix a typo.
2023-08-20 18:19:37 +01:00
cb069d6063
Add the permute op (similar to pytorch). ( #504 )
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* Add the permute op (similar to pytorch).
* Add the backprop for dimension permutation.
2023-08-18 16:30:53 +01:00
a5c5a893aa
add max_pool2d ( #371 )
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Co-authored-by: 赵理山 <ls@zhaolishandeMacBook-Air.local >
2023-08-09 18:05:26 +01:00
2345b8ce3f
Skeleton for the avg-pool2d and upsample-nearest2d ops. ( #337 )
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* Skeleton for the avg-pool2d and upsample-nearest2d ops.
* Preliminary conv2d support.
2023-08-07 16:15:38 +01:00
166bfd5847
Add the recip op + use it in stable-diffusion. ( #331 )
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* Add the recip unary op.
* Fix the cuda kernel.
* Use the recip op in sigmoid.
2023-08-06 21:14:52 +01:00
4b3bd79fbd
Remove the embedding ops in favor of index-select. ( #299 )
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* Remove the embedding ops in favor of index-select.
* Also remove the cuda kernels.
2023-08-02 05:42:11 +01:00
3eb2bc6d07
Softmax numerical stability. ( #267 )
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* Softmax numerical stability.
* Fix the flash-attn test.
2023-07-28 13:13:01 +01:00
89ba005962
Support backprop for a few more ops. ( #254 )
2023-07-26 21:31:54 +01:00
fe87778223
Add the copy op. ( #227 )
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* Add the copy op.
* Tweak some cat error messages.
* Handle the contiguous case in to_vec1.
* Fast variant for to_vec2.
* Add add a faster to_vec3 variant.
2023-07-23 18:06:47 +01:00
52c5d8c087
Add the gather op. ( #219 )
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* Start adding gather.
* Gather cpu implementation + use in simple training.
* Add scatter_add for the gradient of gather.
* Simple cpu implementation of scatter_add.
* Use gather in the simple-training backprop.
2023-07-22 07:21:28 +01:00
6eeea1b04e
Polish the index-add op and use it in the index-select backprop ( #218 )
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* Add the cpu version of index-add.
* More cpu support for index-add.
* Use index-add in the backprop.
2023-07-22 05:31:46 +01:00
27174a82aa
Start adding index-add.
2023-07-21 20:12:48 +01:00
5cc843550d
Add binary and ternary custom ops. ( #217 )
2023-07-21 17:29:50 +01:00
a6bcdfb269
Custom ops with a single argument ( #214 )
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* Add the CustomOp1 trait.
* Add an example of custom op.
* Polish the custom op example.
* Add some backward pass test for custom ops.
2023-07-21 15:18:05 +01:00
410654525f
Refactor the reduce ops in order to introduce argmin/argmax. ( #212 )
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* Refactor the reduce ops in order to introduce argmin/argmax.
* Clippy fixes.
* Use the newly introduced argmax.
* Fix the strided case.
* Handle the non-contiguous case.
2023-07-21 11:41:08 +01:00
c60831aad4
Add more gradient tests + bugfixes. ( #211 )
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* Add more gradient tests + bugfixes.
* More tests and fixes.
* More tests.
2023-07-21 06:52:39 +01:00
4845d5cc64
More realistic training setup. ( #210 )
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* More realistic training setup.
* Compute the model accuracy.
* Very inefficient backprop for index select.
* More backprop.
* Fix some backprop issues.
* Backprop fix.
* Another broadcasting backprop fix.
* Better backprop for reducing ops.
* Training again.
* Add some gradient tests.
* Get the training to work.
2023-07-20 18:25:41 +01:00
fa08fb3126
Add the index-select op. ( #209 )
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* Add the index-select op.
* Cpu implementation of index-select.
* Add the cpu implementation for index-select.
2023-07-20 14:01:03 +01:00
2a8f28d687
Op refactor ( #208 )
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* Add the binary and unary op enums to factorize some code.
* Bugfix.
2023-07-20 12:28:45 +01:00
e9c052bf94
Add the comparison operations. ( #207 )
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* Add the comparison operations.
* Add the helper functions on the tensor side.
* More cmp operations.
* Cpu implementation for the comparison operations.
2023-07-20 09:40:31 +01:00
cb687b4897
Add some more developed training examples. ( #199 )
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* Use contiguous tensors for variables.
* Sketch the mnist example.
* Start adding the reduce ops.
* Renaming.
* Refactor the reduce operations.
* Bugfix for the broadcasting vectorization.
2023-07-19 15:37:52 +01:00
2bfa791336
Use the same default as pytorch for sum. ( #164 )
2023-07-13 21:32:32 +01:00
23e105cd94
Add the gradient for reduce-sum. ( #162 )
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* Add the gradient for reduce-sum.
* And add the gradient for the broadcast ops.
* Add some backprop tests.
* Add some linear regression example.
2023-07-13 20:14:10 +01:00
50b0946a2d
Tensor mutability ( #154 )
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* Working towards tensor mutability.
* Use a ref-cell to provide tensor mutability.
2023-07-13 11:04:40 +01:00
270997a055
Add the elu op. ( #113 )
2023-07-09 21:56:31 +01:00
3aac1047fe
Sketch the conv1d op.
2023-07-04 10:52:34 +01:00
2741b39ad3
Use broadcasted scalars for const tensors.
2023-06-29 11:56:40 +01:00
